Breast Tomosynthesis With Display Of Highlighted Suspected Calcifications

ABSTRACT

Systems and methods that facilitate the presentation and assessment of selected features in projection and/or reconstructed breast images, such as calcifications that meet selected criteria of size, shape, presence in selected slice images, distribution of pixels that could be indicative of calcification relative to other pixels or of other image features of clinical interest.

REFERENCE TO RELATED APPLICATIONS

This application is related to earlier-filed applications Ser. Nos.11/604,069, 11/271,050, 11/059,282, 10/723,486, and 10/305,480 filed,respectively, on Nov. 24, 2006, Nov. 10, 2005, Feb. 16, 2005, Nov. 26,2003, and Nov. 27, 2002, and is related to PCT applicationsPCT/US2005/41941 and PCT2005/42613 filed, respectively, on Nov. 15 and23, 2005. This patent specification hereby incorporates by reference thecontents of each of the earlier-filed patent applications.

FIELD

This patent specification pertains to x-ray tomosynthesis, and morespecifically to techniques and equipment for acquiring, processing,storing and displaying tomosynthesis images, including tomosynthesisprojection images and tomosynthesis reconstructed images. An importantaspect of this patent specification pertains to identifying andhighlighting suspected calcifications in displays of tomosynthesisimages.

BACKGROUND AND SUMMARY OF THE DISCLOSURE

X-ray mammography remains a well-established technology, and x-raytomosynthesis of the breast has been developed recently as discussed inthe earlier-filed patent applications identified above. Clinical testingof tomosynthesis systems has been carried out, and the assignee of thispatent specification, Hologic, Inc., has demonstrated at trade shows inthis country a fused, multimode mammography/tomosynthesis system thattakes either or both types of images, either in single or multiplecompressions/immobilizations of the breast. Dedicated breasttomosynthesis systems also have been proposed.

Tomosynthesis as used in the systems and methods disclosed in thispatent specification typically involves acquiring a plurality oftomosynthesis projection images Tp at respective angles relative to thebreast, and using information describing at least these images Tp (orsome of the Tp images) to reconstruct a plurality of tomosynthesisreconstructed images Tr representative of respective breast slices thathave selective thicknesses and orientations and correspond to respectivesections through or slices of the breast that typically are but need notbe planar. For example, the slices can be curved in 3D space. Inaddition, conventional x-ray mammography images Mp can be acquired, inthe same procedure that acquires the Tp images of a breast or in adifferent procedure and in the same or different compressions of thebreast, and may be used in addition to the Tp images or in place of someof the Tp images, in reconstructing Tr images.

Mp images can be processed by various techniques that draw attention toselected portions or features of these images, such as CAD (computeraided detection) techniques that analyze the images to identify likelyabnormalities and place markers on a breast image or representation thatidentify the location and in some cases the type or other informationabout the likely abnormalities. Some of the parent applicationsidentified above describe applying CAD analysis to Tr and/or Tp imagesas well, or as an alternative or an adjunct to applying CAD to Mpimages, and also describe how to improve the presentations of Tp and/orTr images (collectively referred to here as T images), Mp images, andCAD and/or other information about the images to make the review byhealth professionals more effective and efficient.

CAD application to Mp images also is a well-established technology. See,for example, the mammography CAD products offered by R2 Technology, Inc.of Sunnyvale, Calif. and Patent Publications US 2002/0097902 and US2004/0100476 and U.S. Pat. Nos. 5,970,164, and 6,630,937. In addition tothe disclosure of applying CAD to Tp and Tr images in the relatedapplications identified above, U.S. Pat. No. 6,748,044 discussesapplying CAD to tomosynthesis images and U.S. Pat. No. 7,149,335discusses detecting microcalcifications in tomosynthesis images andsubtracting background to enhance visibility of the detectedmicrocalcifications. Also possibly relevant to state-of-the-art may beUS20030194121A1, U.S. Pat. No. 6,748,044, US20030215120A1,US20050002550A1, US20060269114A1, US20050089205A1, US20050113961A1, U.S.Pat. No. 7,142,633, US20060067473A1, US20060210131A1, US20070003117A1,US20070003118A1, US20070014448A1, US20070052700A1, US20070076928A1. Thepatents and publication identified in this paragraph also areincorporated by reference in this patent specification.

As more information about the breast becomes available from imaging, animportant challenge is to present such information to the healthprofessional effectively and efficiently such that screening forabnormalities can be done thoroughly and effectively, and yet in areasonable time to be practical, and diagnostic assessment can also befacilitated. For a film mammographic study there usually are four filmsof the patient's breasts (at least for studies done in the U.S.A.), twoCC views and 2 MLO views, that typically can be examined within a fewminutes. However, with digital images and particularly tomosynthesisimages Tp and Tr, there can be dozens of images and each can be viewedwithin different windows of pixel values centered at different levels ofpixel values. Unless suitable display techniques are developed,information that is in the images may not be fully appreciated orutilized and/or the examination time may become so long as to beimpractical, particularly for screening asymptomatic patients but alsopossibly for diagnostic or other purposes. This patent specification isdirected to providing tomosynthesis and like images in a manner thatwould facilitate extracting useful information from them in a reasonabletime.

In this patent specification, the notation Mp refers to a conventionalmammogram, which is a two-dimensional x-ray projection image of abreast; the term Mp encompasses both a digital image as acquired by aflat panel detector or another imaging device and the image afterconventional processing to prepare it for display to a healthprofessional or for further processing or for storage, e.g. in the PACSsystem of a hospital or another institution. Mp also encompassesdigitized film/screen mammograms. Tp refers to an image that issimilarly two-dimensional but is taken at a respective tomosynthesisangle between the breast and the origin of the imaging X-rays (typicallythe focal spot of an X-ray tube), and also encompasses the image asacquired as well as the image after being processed for display or forsome other use. Tr refers to an image that is reconstructed from imagesTp, for example in the manner described in said earlier-filed patentapplications, and represents a slice of the breast essentially as itwould appear in a projection X-ray image of that slice at any desiredangle, not only at an angle used for Tp or Mp images. In addition, a Trimage can represent a slice that conforms to any desired surface such asa flat or curved plane. Moreover, the process of reconstructing Trimages can use Mp images in addition to using Tp images or instead ofone or more Tp images. The terms Tp, Tr and Mp also encompassesinformation, in whatever form, that is sufficient to describe such animage for display, further processing, or storage. The images Mp, Tp andTr typically are in digital form before being displayed, and can bedefined by information identifying properties of each pixel in atwo-dimensional array of pixels, although other ways to describe theimages can be used as well or instead. The pixel values typically relateto respective measured or estimated or computed responses to X-rays ofcorresponding volumes in the breast (voxels or columns of tissue). A Trimage can represents a thin slice of a breast, in which case it mayconsist of pixel values representing respective voxels (volume elements)of the breast that are in a single layer or a few layers transverse tothe direction of the x-ray beam, or a Tr image may represent a thickerslice of the breast, in which case the pixel values of the thick-sliceTr image can represent columns of tissue along the direction of thex-ray beam and are calculated using known techniques such as, withoutlimitation, a normalized projection of the pixels of several contiguousthin-slice images onto an image plane, a MW (maximum intensityprojection), or some other way of combining the pixel valuesrepresenting several thin-slice images. As a non-limiting example, athin-slice Tr image can represent a 1 mm thick slice of the imagedbreast and a thick-slice Tr image can represent a 5-20 mm thick slice ofthe breast. Thus, when a breast is compressed for x-ray imaging to athickness of 5-6 cm, there can be 50-60 thin-slice Tr images and 3-12thick-slice Tr images.

Microcalcifications seen in breast images are considered important cluesin screening and/or diagnosis, and prior proposals have been directed toidentifying particular specific patterns of microcalcifications or allmicrocalcifications, or at least those having specified characteristicssuch as size or density. This patent specification takes a differentapproach by not only necessarily seeking to identify and classifypatterns of microcalcification distributions in images, or to identifyor enhance all microcalcifications detectable in the image, but ratherto facilitate the visualization of up to a certain number of selectedsuspected calcifications that meet various special thresholds in a givenimage or volume of tissue in ways that are particularly useful to thehealth professional. Calcifications often have a typical x-rayabsorption characteristic, but not all objects with these absorptioncharacteristics are calcifications or are of clinical value.Calcifications of clinical interest generally fall in a certain range ofsizes and shapes and patterns. The largest calcifications are oftenbenign. Linear ones also are often benign. Identifying all of the verysmallest calcification-like objects runs the risk that some of themmight represent noise and not true calcifications or reasonablysuspected calcifications. One object of the approach disclosed in thispatent specification is to reduce the number of identified possible orsuspected calcifications which are of lower clinical value.

As one non-limiting example, the approach disclosed in this patentspecification involves examining through computer processing theindividual Tr images in a 3D set of such images to identify an initialset of possible calcifications that meets a threshold limiting thenumber of identified calcifications in a given Tr image, or in theentire 3D set or a selected subset of the entire 3D set, to a specifiednumber of calcifications and/or number of pixels that are determined tocorrespond to calcifications. Preferably, the Tr images are presentedfor this examination after filtering with a mask that enhances highspatial frequency image features. The process removes from the initialset, pixels initially determined to relate to calcifications that aretoo large in area or too long in linear extent, and may additionallyimpose other constraints such as excluding initially determinedcalcifications that are not present in two adjacent Tr images, applyingligament removal and edge removal techniques, requiring at least acertain number of calcifications to be in a specified volume of the 3Dset, and excluding calcifications that are in the initial and trailingTr images in a stack of Tr images and thus are likely to be at the skinlevel and unlikely to have clinical significance. The removal processesare designed to remove calcifications that are likely to be devoid ofclinical interest and to remove noise and other non-calcificationobjects. In displaying the results, one example is to show a scout viewthat generally conforms in shape to a projection of the breast and showsa distribution of identified calcifications as well as a current levelthat both (1) includes calcifications and (2) corresponds to a Tr imagethat is orthogonal to the scout image and is seen at a main imagedisplay. Alternatively, this information can be displayed using a ruleror other schematic display that does not conform in shape to aprojection of the breast but still allows display of the current leveland/or the locations of likely calcifications. Thus, the current levelin the 2D scout or schematic view points to one or more corresponding Trimages. The scout or schematic view also shows a pointer to a next levelthat contains identified calcifications so that a user can convenientlyclick on that level and thus call on the main display the next Tr imageof interest. The scout or schematic view may also indicate how manycalcification clusters are in a given Tr image. In addition, the usercan toggle the main display between showing a Tr image with or withouthighlighted calcifications therein. A health professional thus canquickly and effectively review Tr images that are likely to be ofinterest. The health professional can additionally select for the maindisplay additional Tr images, Tr images that are for thick or thinslices and/or reconstructed in another orientation, Tp images and/or Mpimages.

An alternative or additional process is to initially search Tp and/or Mpimages rather than the 3D set of Tr images to identify likelycalcifications of interest. This can be done using CAD as disclosed inthe patent literature incorporated by reference in this patentspecification, or by adapting the principles discussed above foridentifying calcifications in Tr images and 3D volumes, or in some othermanner. After likely calcifications of clinical significance areidentified in the 2D Tp and/or Mp images, the 2D images can be displayedone at a time or several at a time, or only those 2D images that haveidentified calcifications can be displayed. When a user points to alikely calcification in a displayed 2D image, e.g., by a mouse click onthe calcification in a 2D image, computer processing can search throughthe Tr images of the breast to identify and display the Tr image or Trimages that contain that calcification. This search through the Trimages can use knowledge about the location of the likely calcificationin the 2D image, on parameters of the calcification such as its size,shape, pixel values and distribution of those values in the 2D image,and possibly other parameters. In case of an ambiguity, i.e., thecalcification pointed to in the 2D image appears in two or more Trimages, all possibly relevant Tr images can be displayed to the user,singly or in a set or subsets or in cine mode, and the user may selectfor further use the ones that appear relevant or dismiss any that arenot. This alternative can reduce processing time because the search forlikely calcifications in the 2D images can be faster, and the subsequentsearch for the Tr slice(s) that contain a calcification to which theuser pointed in a 2D image also can be faster. One reason for greatercomputational efficiency is that the 3D data set (the Tr images) need tobe processed only after a likely calcification has been selected, soonly a relatively small volume of the 3D set would need to be searched.Another advantage of this alternative may be if the search process ismore sensitive and/or more accurate for 2D images. If so, then it ismore likely to decrease the overall rate of false negatives and/or falsepositives in identifying likely calcifications, and thus improve thepresentation of images to the health professional and make the overallprocess of assessing the images for screening, diagnosis, or otherpurposes, more effective and/or more efficient.

As another alternative or additional process, the user can point to anyfeature in one of the 2D images, not necessarily a likely calcification,even in 2D images that have not been processed to identify likelycalcifications, and the process can attempt to identify and display forthe user the Tr slice(s) in which that feature can be seen well, e.g.,the feature is in best focus. The search through the 3D set of pixeldata can use information about the feature to which the user pointed,such as location in the 2D image, size, shape, pixel values anddistribution of those values, and possibly other parameters. If thefeature is relatively unique and small, the process may correctlyidentify and display for the user one or only a few Tr slices. In othercases, such as in the case of a relatively large mass, or in the case ofa feature in the 2D image that represents a superposition of two or morefeatures in the breast that are along the x-ray beam path to thatfeature in the 2D image, there may be ambiguities as to which Tr imageor images show the feature to which the user has pointed. Again, in sucha case the process may similarly display the possibly pertinent Trslices, or may display only those that meet a threshold of relevance,e.g., based on a calculation of their degree of relevance to the featureto which the user pointed.

The discussion above refers to highlighting calcifications. Othermethods of emphasizing calcifications also are possible, and are in thescope of this patent specification. These include pointers such asarrows, circling or drawing lines, and the use of changing the color ofthe display of the calcification, or other methods of presenting visualcues to the viewer to look at specified areas on the image.+

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of a display of a scout image and areconstructed tomosynthesis slice image Tr.

FIG. 2 illustrates in block diagram form a mammography/tomosynthesissystem that can be used to acquire breast imaging x-ray data and processand display the data according to preferred embodiments of the approachdisclosed in this patent specification.

FIG. 3 is a flowchart illustrating an embodiment of a new process.

FIG. 4 illustrates a method of displaying a current slice and locationsof calcifications.

FIG. 5 illustrates a method of identifying calcifications on atomosynthesis slice image Tr.

DETAILED DESCRIPTION

Referring to FIG. 1, the image on the left is a scout view 10 thatgenerally conforms to an outline of a patient's breast and containsbright dots indicative of calcifications identified through a processdescribed below. Two facing arrows 12 a and 12 b at the side of scoutimage 10 point to a level in the scout image that corresponds to areconstructed tomosynthesis slice image Tr 12 seen at the right side ofFIG. 1. The views of images 10 and 12 are mutually orthogonal. Tr image12 in this example has highlighted calcifications (seen as white dots)that are more numerous than those seen in scout image 10, for reasonsthat will become apparent from the disclosure below. Next to scout image10 are an arrow 14 that points to the next level up in image 10 thatcontains calcifications and an arrow 16 that points to the next levelbelow in image 10 that contains calcifications. By clicking on arrow 14or arrow 16 the user can call for display at 12 the corresponding Trimage. Tr image 12 can be displayed without highlighting its suspectedcalcifications, as a normal Tr image, by a user command such as clickinga mouse button or through some other interface. The Tr image that isdisplayed as image 12 can be for a thin slice, e.g., a 1 mm or somewhatthinner or thicker slice of breast tissue, or for a thick slice such asa 3 mm or somewhat thinner or thicker slice of breast tissue, in whichcase the thick-slice image can be formed by combining several thin sliceTr image through a known process such as, without limitation, addingwith or without normalization, MIP projection, etc. Alternatively, datarepresenting Tp images can be reconstructed into data representingthick-slice Tr images in the reconstruction process using knowntechniques such as using appropriate backprojection or frequency domainfilters. The user can click on button 13 a, 13 b and 13 c to toggledisplay 12 between a Tr image with and without highlighted suspectedcalcification, or to the previous and next Tr images.

FIG. 4 shows an alternative method to the scout view for identifyingslice locations for calcifications. This involves a ruler that indicatesboth the currently-displayed slice, in terms of its height or positionin a stack of Tr images and corresponding slices of breast tissue (usinga marker such as the one labeled “Slice position indicator” in FIG. 4),and also Calcification slice indicator marks that show the slices wherepotential calcifications have been identified (by marks such as thearrows labeled “Calcification slice indicator” in FIG. 4).

FIG. 5 shows an alternative method for identifying calcifications thatdoes not require highlighting them. In this figure, potentialcalcifications are outlined by a box such as the one labeled “Squareindicating calcifications” in FIG. 5. Arrows pointing to thecalcifications would be an alternative method, as would other marks andor lines and or color and/or intensity changes on the image in thevicinity of the calcifications.

X-ray data for use in the process disclosed in this patent specificationcan be acquired, processed, and displayed by the system illustrated inFIG. 2 as a high level integration of sub-systems discussed in greaterdetail in the documents incorporated by reference in this patentspecification. In FIG. 2, an x-ray data acquisition unit 100 includes anx-ray source 110 imaging a patient's breast 112 supported on a breastplatform 114. An x-ray imager 116 such as a flat panel, directconversion imager available from Hologic, Inc. of Bedford, Mass.,generates projection image data such as data defining images Mp and/orTp. X-ray source 110 is mounted for movement around breast platform 114so that images Tp (and Mp, if desired) can be taken at a number ofdifferent angles for a specific orientation of breast platform 114, suchas a generally CC orientation or a generally MLO orientation. X-rayimager 116 can be stationary but preferably it also moves relative tobreast platform 114, in a specified synchronous relationship to source110, preferably in a manner that keeps the imaging plane at the sameangle to the imaging x-ray beam. Units 110 and 116 communicate withx-ray data acquisition control 118 that controls the operation of thesystem as known from said material incorporated by reference. X-ray datafrom imager 116 is delivered to processing and image reconstruction unit120 that includes one or more programmed digital computers, where datais processed as known into Tp and possibly Mp images and into Tr imagesand where the process described below is carried out. The resultinginformation is displayed at image display unit 122. The software for anyspecific implementation of specific data processing hardware can bewritten without undue experimentation by a person skilled in the artbased on the disclosure of this patent specification. The details ofsuch implementation would depend to a certain extent on factors such asthe hardware and operating systems that a particular designer or userwould select, and many variations are possible. For the sake of bothclarity and conciseness such details that are within the skill of theart once the disclosure herein is available, are not included in thispatent specification.

The processing carried out by unit 120 typically includes knownfiltering and preliminary processing of the Tp image data (and any Mpdata used in addition to or instead of Tp image data) and reconstructionof thin and/or thick slice Tr image data that defines a 3D set of pixelvalues. The 3D set is made up of the pixel values representing an x-rayproperty of respective pixels of each of a number of Tr images, each Trimage representing a respective slice of breast tissue. Preferably, theTr images used in steps 1-4 below represent thin slices of the breast,such as 1 mm slices, but using thicker slice images is not excluded.These pixel values are processed in the following principal steps as anon-limiting preferred example following a filtering of the Tr imagesindividually to suppress low spatial frequency components. Any one of anumber of known filtering processes can be used, such as a processinvolving the use of unsharp mask filters.

-   -   1. Compute and use a threshold to form a first provisional set        of pixels that are candidates for inclusion in a final set of        pixels that are determined to be associated with calcifications        and called “calc pixels” below. The objective is to include in        the final set of calc pixels no more than a selected number N of        pixels for the entire 3D set of pixels defining the Tr images.        For example, candidate calc pixels can be identified in this        step by provisionally identifying as calc pixels the pixels that        have pixel values exceeding a provisional threshold level. This        can be done by processing only the pixel values in one or        several Tr images that may correspond to centrally located        breast tissue, or it can be done for the entire 3D set. As a        non-limiting example, if pixel values in a particular system are        adjusted to range from −60 to +60 units in value in a Tr image        after filtering per step 1 above, any pixel that has a value        greater than, e.g., 40 can be provisionally classified as a calc        pixel in a first iteration. If the total number of candidate        calc pixels found in the Tr image in the first iteration is too        large (as a non-limiting example, more than 150) then the        provisional threshold of 40 is raised, e.g., to 41, and the        process is repeated to provisionally classify as candidate calc        pixel those having pixel values greater than 41. If the initial        iteration yields a total number of calc pixels that is too low        (as a non-limiting example, less than 50) the initial threshold        is lowered, e.g., to 39, and the process is repeated. These        iterations are repeated until the total number of candidate calc        pixels is in the desired range, for example and without        limitation, in the range of 50 to 150 calc pixels for the given        Tr image. The specific initial threshold, the size of the steps        by which it is raised or lowered, and the desired range of total        number of candidate calc pixels can be set depending on user        preferences, either as part of the design process or as a        parameter that can be set by service personnel or by the user of        the system in the field, or on the basis of a study of typical        values for a large population of breast images. This step yields        a first provisional set of calc pixels.    -   2. Form a second provisional set of candidate pixels by        excluding those associated with large areas in a Tr image that        contain contiguous, i.e., connected, or nearly contiguous        candidate calc pixels. As a non-limiting example, exclude from        the first provisional set the candidate calc pixels associated        with areas greater than 0.31 square mm (e.g. an area of about 30        pixels). The test can be for an area of only contiguous pixels        provisionally identified as calc pixels, or it can be for areas        in which any provisionally identified calc pixel is spaced by no        more than one (or a set multiple of) pixels that are not calc        pixels. This removes calcifications that would be clearly        visible, or of little clinical relevance, in a Tr image so there        is no need to point them out to the health professional and,        moreover, if left in the displayed images they might obscure        other, smaller calcification that should be pointed out.    -   3. Form a third provisional set of calc pixels by removing from        the second provisional set the pixels that are generally        arranged in lines that have excessive lengths. These linear        groups of candidate calc pixels may be associated with blood        vessels or other structures that may be of less interest than        other calcifications. For example, a line of contiguous or        nearly contiguous candidate calc pixels that is more than 2-4 mm        long may be considered too long in this step. The term nearly        contiguous is used in this patent specification to denote calc        pixels that might be separated by one (or a set multiple of)        non-calc pixels.    -   4. Form a fourth provisional set of calc pixels by removing from        the third set the candidate calc pixels that do not have as        contiguous neighbors, candidate calc pixels in at least two        adjacent Tr images, as they are likely to be image noise.    -   5. Combine the thin-slice Tr images that still have candidate        calc pixels into thick-slice Tr images to facilitate volume        analysis. As a non-limiting example, add and if desired        normalize, each set of three contiguous Tr images into a        respective thick-slice Tr image by forming a new pixel by adding        the values of three contiguous pixels in a direction transverse        to the planes of the Tr images and dividing the result by three.        As an alternative, combine into a thick-slice Tr image the        several Tr images that contain candidate calc pixels forming in        3D a clump of candidate calc pixels, e.g., a 3D clump of        candidate calc pixels that have at least a specified density        (ratio of all pixels to candidate calc pixels, or the reverse).    -   6. Form a fifth set of candidate calc pixels by removing from        the fourth set the candidate calc pixels that are arranged in        lines that are too long in any direction (e.g. more than 2-4 mm)        in a thick-slice Tr image and, therefore, are likely to be        associated with structures such as ligaments, blood vessels, or        cyst walls.    -   7. Form a sixth set of candidate calc pixels by eliminating from        the fifth set the candidate calc pixels that are not in a set of        at least a specified number of candidate calc pixels in a        specified volume of the 3D set of pixels, e.g., in a volume that        represents a 1 cm by 1 cm by 3 mm volume of the breast, where        the 3 mm is the size of the thick slice Tr image.    -   8. Form a seventh set of candidate calc pixels by eliminating        from the sixth set the candidate calc pixels that are too low in        density in the 3D volume of pixels. For example, eliminate        candidate calc pixels that are in a volume of the 3D set of        pixels of a specified size in which there is too low a ratio        of (a) total number of calc pixels in the volume to (b) the        number of candidate calcs, where a candidate calc consists of        connected calc pixels. As a non-limiting example, a ratio less        than 1.1 in a volume of 1 cm by 1 cm by 3 mm can be considered        too low. This step tends to eliminate candidate calcs that may        represent image noise.    -   9. Form a final set of calc pixels by eliminating from the        seventh set the candidate calc pixels that are in the first and        last set of Tr images, as they are likely to correspond to        pixels related to breast skin. As a non-limiting example, the        candidate calc pixels from the first and last 1-3 Tr images in a        stack of Tr images may be eliminated in this step.    -   10. Project the final set of calc pixels onto an image plane        that is orthogonal to the planes of the Tr images to thereby        form a scout image such as image 10 in FIG. 1. If desired,        enhance the projected calc pixels so that they would stand out        better in image 10. For example, increase the pixel values of        the calc pixels in the final set to a higher value so that they        appear as brighter spots in the scout image and/or increase the        sizes of spots in the scout image that represent determined        calcifications by setting to a higher or highest pixel value the        pixels that are within a specified distance from a calc pixel        that is in the final set.    -   11. Provide user interface and interaction between arrows in the        scout images 10 and Tr images 12 for display as in FIG. 1, for        example by including in display unit 122 appropriate user        interface devices such as a mouse or other pointer to enable the        user to click on selected arrows in image 10 and to make the        system respond to the clicks as described above_([c1]).    -   12. Selectively enhance calcifications in images 12, by        increasing their brightness and/or size, comparable to the        enhancement of the scout image 10 described in step 11 above.    -   13. Provide for user interaction in selecting display of images        12 with or without such enhancement by higher brightness of        pixels representing calcifications in images 12, for example by        including in display unit 122 appropriate user interface devices        such as a mouse or other pointer to enable the user to click on        image 12 or some other display portion to toggle between a Tr        image with or without enhanced calcifications and/or to toggle        between the display of a thin-slice Tr image and the display of        a thick-slice Tr image. For example, a thin-slice Tr image can        represent a 1 mm thick slice of breast tissue while a        thick-slice Tr image can represent a 3 mm or thicker slice of        breast tissue_([c2]).    -   14. Provide for user interaction in selecting display of images        12 with or without such enhancement by higher brightness of        pixels representing calcifications in images 12, by slabbing a        given number of slices to form a thick slice. In slabbing, the        calc pixels may be slabbed independently of the image pixels        that are not identified as calc pixels. The term “slabbing” is        used here in the sense of “combining” or “integrating”        parameters of the pixels of images representing thinner slices        into pixels of an image representing a thicker slice. Various        known slabbing techniques can be used such as averaging with or        without normality after, median, mode, maximum, MIP and/or other        operations for collapsing columns of pixels.    -   15. Provide for user interaction in selecting display of images        12 with or without such enhancement by higher brightness of        pixels representing calcifications in images 12, by slabbing        calc pixels belonging to an identified cluster, where the        slabbed calc pixels are shown on a specified slice. The image        pixels that are not calc pixels, in those slices that contain        calc pixels, may or may not be slabbed.

FIG. 3 illustrates a particular implementation of a process related tothe above-described example. The process of FIG. 3 starts with inputtingdata describing the reconstructed images Tr for a given view, e.g., theTr images reconstructed from the Tp images taken when the breast isimaged in a position suitable for a CC or an MLO view. The numberedsteps discussed below correspond to the blocks of FIG. 3.

3-1. Initialization

The input Tr images are reconstructed images representing breast tissueslices, where the pixel values outside the breast area are constant(i.e., the image has been masked by previous processing). Duringinitialization global parameters are defined, and adjusted for pixelsize, and memory is allocated to process the given Mammographic View;which in this case is a Tr image. A global threshold is defined using aspecified slice, for example, the center slice in the stack (View) asfollows.

-   -   1. From input slice image O_(i), where the subscript refers to        the slice number, create smooth slice image, S_(i) using a 5×5        boxcar filter)    -   2. Create Unsharp mask image U_(i)=O_(i)−S_(i), where the        typical range of values in U_(i) is −60 to +60    -   3. Threshold images U_(i) with fixed initial threshold of 40 to        produce binary image B_(i)        -   B_(i)=0 if U_(i)<40        -   B_(i)=1 if U_(i)>=40    -   4. Label pixels in B_(i) to produce Label image L_(i) (the label        image assigns a unique label to any connected positive value        pixels in B)    -   5. Calculate label density as follows

Labdense=(Nlab/bfrac)

-   -   -   bfrac=# of pixels in breast/total number of pixels        -   Nlab=number of labels

    -   Check if Labdense is within a specified fixed range and adjust        the threshold if needed as follows. If Labdense<LabdenseMin,        lower the threshold by 1.0 If Labdense>=LabdenseMax, raise the        threshold by 1.0

    -   Where LabdenseMin=1000 and LabdenseMaz=2500

If Labdense is within the range, return initial threshold. If outsiderange, iterate steps 3-5, adjusting threshold, until within range. Themaximum allowed iterations is 15.

The resultant threshold is used for all subsequent slices. Note that themethod for calculating threshold can also be used for each sliceseparately.

3-2. Locate Candidate Pixels per Slice

Create Label image for each Tr slice image using steps 1-4 in Section 1.The first and last 3 Tr slice images, near the skin surfaces, are notincluded in the calculation to rule out skin-calcs.

Subject the label image to the following ‘Cuts’.

-   -   1. Pixel Population Cut        -   Delete labels that have more than Nmax pixels where            -   Nmax=MaxPixArea/PixSize²            -   PixSize=size of pixels in mm            -   MaxPixArea=0.3 mm²    -   2. Range Cut        -   a. Calculate the linear extent of labels in x and y        -   b. Delete labels that have an extent (in either direction)            larger than 0.63 mm    -   3. Boundary Cut        -   a. Delete labels that are close to the breast boundary.            Currently, if a label pixel is within 3 mm of the skin edge,            it is deleted.

Perform the logical AND of the new label image (after being subject tothe previous cuts) and previous slice label image L_(i-1) to producebinary image K.

-   -   K_(i)=L_(i) && L_(i-1)

3-3. Slab and Re-Label

The candidate image K_(i) is ‘slabbed’ (as a non-limiting example, addedon a per pixel basis) with adjacent slices to give binary Slab imageS_(i). The slabbing is per pixel and uses 3 contiguous slices.

$\begin{matrix}{S_{i} = {{1\mspace{14mu} {if}\mspace{14mu} {{SUM}\left( {K_{i - 1},K_{i},K_{i + 1}} \right)}} > 0}} \\{= {0\mspace{14mu} {otherwise}}}\end{matrix}$

A running sum may be used for efficiency if the Tr slice images areinput consecutively. In the running sum method, the first slice of theprevious slab is subtracted and the current slice is added to the slabimage. S_(i) is then Re-labeled to give new label image M_(i).

3-4. Pre Group Pixel Cuts

Apply additional Cuts to Label image M computed in step 3

4.1 Single Pixel Cut

Delete single pixel candidates with very low attenuation, i.e., on thevisual threshold, or possible noise. Let the image pixel value of M beV_(j) where j is the image pixel index (0<j<Nxy), and Nxy is the totalnumber of pixels per slice. For each identified calc pixel j, calculateN_(g) as follows

N_(g)=Σ_(k)(f×{1, if V_(j)>V_(j+k) 0, if V_(j)≦V_(j+k)}

-   -   where k={−2,2,2*Nx,−2*Nx,1−Nx,−1−Nx,1+Nx,Nx−1}    -   f=1.04    -   Nx=number of columns in the image.    -   if N_(g)<8, unset Label pixel j in M.

4.2 Edge Cut

Remove label pixels that are located on edges, e.g., ligaments, artifactedges, breast skin folds.

-   -   1. Search for peaks in pixel intensity along x direction        starting with candidate labeled pixel as center. The search        distance is ±0.8 mm from the center labeled pixel. Extract a        line L of pixel values along the x-dimension with the center        point being a calc pixel. The length of L is I mm.    -   2. Calculate the peak (maximum value) and maximum derivative        value, L_(i)−L_(i-1), of L.    -   3. If peak is above a threshold (=30), count as valid peak.    -   4. Repeat steps 2-4 for pixel centers located at ±N        (perpendicular to line L) from the calc pixel, where N=0.8        mm/(pixel size). Sum the number of valid peaks and calculate the        average maximum derivative.    -   5. If number of valid peaks is above the maximum (=1.6 mm/(pixel        size)−1) unset the calc Label pixel in M    -   6. If average maximum derivative is above a threshold (=150),        unset calc Label pixel in M.    -   7. Repeat steps 1-7 searching along the y direction instead        of x. The lines L being along the y-direction.    -   8. Repeat steps 1-8 for all labeled pixels.

3-5. Per Slice Grouping

Apply group (cluster) criteria.

For each Valid label in M_(j) that passed all previous cuts:

-   -   1. Search neighborhood (±5 mm) and sum all Labels. If sum is        greater than 2, assign a group label, otherwise unset Label.        This keeps all clusters of 3 calcs within a 1 mm square.

5.1 Post-Group Cuts

After group Labels have been assigned, apply additional cuts to eachgroup.

-   -   1. Calculate Calc Pixel Density, CPD

CPD=(Number of pixels in group)÷(Number of labels (calcs) in group)

-   -   2. If CPD≧CPD_(min)(=3), do not apply any additional cuts, and        do not delete the group.    -   3. If CPD<CPD_(min) apply the following cuts in order.    -   3.1 If CPD<1.1, delete group. Otherwise proceed with Cut 3.2    -   3.2 Calculate Δ_(nn)

Δ_(nn)=Ave(C)−Ave(N)

-   -   -   Ave(C)=average pixel value of labels in the group.        -   Ave(N)=average pixel value of neighboring pixels (nearest            neighbors of C)

In the average calculations only labels that have less than 3 pixels areconsidered. If the number of labels used in the average is greater than0.6×(total number of labels in group), apply the following cuts.

-   -   If (Δ_(nn)<25) delete group    -   If (Δ_(nn)<42 && CPD<1.7) delete group

If group not deleted proceed with Cut 3.3.

-   -   3.3 Fit a 3^(rd) order polynomial to the distribution of labels        within the group. If the x-extent of the group is greater than        the y-extent, x is the dependent variable, otherwise y is the        dependent variable. Calculate the normalized chi-squared of the        fit,

Nchi=chi-squared÷Number of points used in lit

-   -   -   If Nchi<0.10 delete group

3-6. Volume Grouping

Regroup the valid labels in the volume (slice stack) such that labeledpixels that are within ±10 mm in x,y, and ±5 mm in z, are in the samegroup. This connects groups that may exist over several slices and maycontain a slice with no labeled pixels. This step combines the previousper slice groups that may overlap (or be close) in the volume.

3-7. Slices of Interest

Calculate the SOI's ‘slices of interest’ for the view. SOI's are thoseslices which may be used in the Viewing application that will allow theuser to quickly scroll the TCE identified slices within a View.

A SOI is defined for each identified group as the slice that containsthe most labeled pixels in that group. Note that 2 different groups mayhave the same SOI.

Some other possible methods include:

-   -   1. Finding calcifications using the Tp data, and identifying the        calcification locations on the Tr dataset for display, as        described.    -   2. Finding calcifications using both the Tp and the Tr data, and        identifying the calcification locations on the Tr dataset for        display as described. Using both Tp and Tr may improve the        accuracy or computational efficiency of the calc determination        algorithm_([c3]). Methods for identifying calcifications in Tp        are known, such as shown in the material incorporated by        reference herein. Once potential calcifications in Tp are found,        their possible locations in Tr can be determined through        reconstruction of the locations found in the Tp images, such as        described in the material incorporated by reference herein.    -   3. A similar method can be used to identify possible pathology        masses, and lesions containing both masses and calcs. Methods of        identifying possible pathology masses are given in the material,        herein incorporated by reference. An inventive feature here is        the user interface whereby only slices are shown that have        either masses or calcs or both. The CAD algorithm can use either        Tr or Tp or both datasets to do its determination.    -   4. In the above-described approach, the display of a given slice        might contain calcifications (or masses) from other slices,        especially if they have been ascertained to be part of the same        cluster. If desired, a different highlighting can be applied to        calcs or masses that also are present in adjacent Tr slices that        are not displayed at the moment.    -   5. Instead of displaying only breast slice images that include        pixels determined to be calcifications, display all breast slice        images or at least a subset of all breast slice images,        including some that do not have such pixels, such that the user        can scroll through those images. The user can be helped to        identify the calc pixels, particularly if their brightness is        enhanced as discussed above, by the sudden change in brightness        in scrolling from one displayed slice image to the next or help        can be provided by marking the calc, e.g. with some symbol. Then        change from one slice image to another can be directed manually        by the user, or the display can be automated to present the        succession of slice images in cine format.    -   6. Instead of or in addition to identifying talcs, the process        can be adapted to identify masses using for example CAD        techniques such as those described in the material incorporated        in this patent specification by reference. Suspected        abnormalities can then be selectively specified to be (1) only        calcifications, (2) only masses, and (3) both calcifications and        masses. The selection and display of masses can then be similar        to the selection and display of calcifications described above.    -   7. Instead of the process described above to identify        abnormalities corresponding to suspected calcifications, a        simpler process can be used such as a filter that identifies all        pixels in a Tp and/or Tr image that meet specified threshold        criteria of pixel values selected to identify pixels likely to        correspond to calcifications. Known techniques can be used to        eliminate from an initial cut those abnormalities that are        likely to represent noise, such as isolated single pixels that        meet the threshold criteria or very small groups of such pixels.        The remaining suspected abnormalities can then be displayed as        described above.

An alternative or additional process involves finding likelycalcification in the individual 2D Tp and/or Mp images and thensearching only subsets of the 3D Tr images to select corresponding Trimages for selective display to the user. This can be implemented byinitially searching Tp and/or Mp images rather than the 3D set of Trimages to identify likely calcifications of interest. The initial searchof 2D images can be done using CAD as disclosed in the patent literatureincorporated by reference in this patent specification, or by adaptingthe principles discussed above for identifying calcifications in Trimages and 3D volumes, or in some other manner. After likelycalcifications of clinical significance are identified in the 2D Tpand/or Mp images, the 2D images can be displayed one at a time orseveral at a time, or only those 2D images that have identifiedcalcifications can be displayed. When a user points to a likelycalcification in a displayed 2D image, e.g., by a mouse click on thecalcification in a 2D image, computer processing can search through theTr images of the breast to identify and display the Tr image or Trimages that contain that calcification. This search through the Trimages can use knowledge about the location of the likely calcificationin the 2D image, on parameters of the calcification such as its size,shape, pixel values and distribution of those values in the 2D image,and possibly other parameters. In case of an ambiguity, i.e., thecalcification pointed to in the 2D image appears in two or more Trimages, all possibly relevant Tr images can be displayed to the user,singly or in a set or subsets or in cine mode, and the user may selectfor further use the ones that appear relevant or dismiss any that arenot. This alternative can reduce processing time because the search forlikely calcifications in the 2D images can be faster, and the subsequentsearch for the Tr slice(s) that contain a calcification to which theuser pointed in a 2D image also can be faster. One reason for greatercomputational efficiency is that the 3D data set (the Tr images) need tobe processed only after a likely calcification has been selected, soonly a relatively small volume of the 3D set would need to be searched.Another advantage of this alternative may be if the search process ismore sensitive and/or more accurate for 2D images. If so, then it ismore likely to decrease the overall rate of false negatives and/or falsepositives in identifying likely calcifications, and thus improve thepresentation of images to the health professional and make the overallprocess of assessing the images for screening, diagnosis, or otherpurposes, more effective anti/or more efficient.

As another alternative or additional process, the user can point to anyfeature in one of the 2D images, not necessarily a likely calcification,even in 2D images that have not been processed to identify likelycalcifications, and the process can attempt to identify and display forthe user the Tr slice(s) in which that feature can be seen well, e.g.,the feature is in best focus. The search through the 3D set of pixeldata can use information about the feature to which the user pointed,such as location in the 2D image, size, shape, pixel values anddistribution of those values, and possibly other parameters. If thefeature is relatively unique and small, the process may correctlyidentify and display for the user one or only a few Tr slices. In othercases, such as in the case of a relatively large mass, or in the case ofa feature in the 2D image that represents a superposition of two or morefeatures in the breast that are along the x-ray beam path to thatfeature in the 2D image, there may be ambiguities as to which Tr imageor images show the feature to which the user has pointed. Again, in sucha case the process may similarly display the possibly pertinent Trslices, or may display only those that meet a threshold of relevance,e.g., based on a calculation of their degree of relevance to the featureto which the user pointed.

The examples described above are only illustrative and other examplesalso are encompassed within the scope of the appended claims. Theparameters given as example above, such as initial thresholds, sizes ofareas or volumes, etc. can be modified by those skilled in the artwithout departing from the invention described in the appended claims.Other variations can be introduced without departing from the spirit ofthe disclosure or from the scope of the appended claims. For example,elements and/or features of different illustrative embodiments may becombined with each other and/or substituted for each other, and thesteps of the example described in detail above can be rearranged andsteps can be omitted or added within the scope of this disclosure andappended claims.

1. A method of acquiring and displaying x-ray images comprising:acquiring x-ray tomosynthesis image data Tp representative of projectionimages Tp taken at different angles of an origin of imaging x-raysrelative to a patient's breast; reconstructing at least a subset of theacquired Tp data into reconstructed tomosynthesis image data Trrepresentative of images Tr of slices of the breasts that have selectedorientations and thicknesses; identifying calcifications that meetselected criteria of number, size, location and other properties byprocessing said Tr data; and selectively displaying a representation ofthe identified calcifications in association with displaying selectedimages related to said Tr data. 2-35. (canceled)